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is a principal scientist at FFI, while Andreas Austeng is a professor at UiO. I am employed at FFI, where I started in 1998 after receiving my degree of Cand. Scient. in Physics from the University of Bergen. The work on the thesis was conducted as a part of my job over the years 2011 -2021, and was funded by FFI's projects on synthetic aperture sonar (SAS). These SAS projects have been run and financed through a collaboration between FFI, Kongsberg Maritime and the Royal Norwegian Navy. This thesis includes a collection of five papers, placed and presented in a larger common perspective. I first place the title topic of "Advanced SAS" in a greater context. Then I present each of the individual papers, and give an updated review on their topics. I follow up with a discussion on my contributions in a greater perspective, before I summarize my findings and conclude.

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Synthetic Aperture Sonar (SAS) is a technique which delivers sonar images of the seabed with both high resolution and large area coverage rate. SAS is therefore a well suited sensor for search of small objects on the seafloor, and is an important tool in many emerging mine countermeasures (MCM) systems. An interferometric SAS system can also resolve the angle of arrival in the vertical plane, and thus estimate the depth of an object. In this talk, we present techniques using SAS imaging for depth estimation of small objects, not on the seafloor, but located in the water column. We consider the effect of geometry, sensor settings and processing parameters. For objects of interest, we present a belief propagation inspired method for estimating the depth of the objects. This method is CPU intensive, but avoids the phase ambiguity problem encountered in standard SAS interferometry. We compare this method to a coarse depth estimate acquired from the multipath response in the SAS images as well as to ground truth. We show example images and depth estimates from the Kongsberg HISAS interferometric SAS collected by a HUGIN autonomous underwater vehicle.